A Simple Overview of Pancreatic Cancer Treatment for Clinical Oncologists.
Ingrid GarajovàMarianna PeroniFabio GelsominoFrancesco LeonardiPublished in: Current oncology (Toronto, Ont.) (2023)
Pancreatic cancer (PDAC) is one of the most aggressive solid tumors and is showing increasing incidence. The aim of our review is to provide practical help for all clinical oncologists and to summarize the current management of PDAC using a simple "ABC method" (A-anatomical resectability, B-biological resectability and C-clinical conditions). For anatomically resectable PDAC without any high-risk factors (biological or conditional), the actual standard of care is represented by surgery followed by adjuvant chemotherapy. The remaining PDAC patients should all be treated with initial systemic therapy, though the intent for each is different: for borderline resectable patients, the intent is neoadjuvant; for locally advanced patients, the intent is conversion; and for metastatic PDAC patients, the intent remains just palliative. The actual standard of care in first-line therapy is represented by two regimens: FOLFIRINOX and gemcitabine/nab-paclitaxel. Recently, NALIRIFOX showed positive results over gemcitabine/nab-paclitaxel. There are limited data for maintenance therapy after first-line treatment, though 5-FU or FOLFIRI after initial FOLFIRINOX, and gemcitabine, after initial gemcitabine/nab-paclitaxel, might be considered. We also dedicate space to special rare conditions, such as PDAC with germline BRCA mutations, pancreatic acinar cell carcinoma and adenosquamous carcinoma of the pancreas, with few clinically relevant remarks.
Keyphrases
- end stage renal disease
- ejection fraction
- newly diagnosed
- risk factors
- locally advanced
- healthcare
- palliative care
- small cell lung cancer
- peritoneal dialysis
- stem cells
- minimally invasive
- mesenchymal stem cells
- lymph node
- coronary artery disease
- oxidative stress
- acute coronary syndrome
- dna damage
- electronic health record
- patient reported
- artificial intelligence
- replacement therapy
- deep learning